• Journal of Environmental Impact Assessment
• /
• v.24 no.5
• /
• pp.456-471
• /
• 2015

Emission source term is one of the strong controlling factors for the air quality simulation capability, particularly over the urban area. Ulsan is an industrial area and frequently required to simulate for environmental assessment. In this study, two CAPSS (Clean Air Policy Support System) emission data; CAPSS-2003 and CAPSS-2010 in Ulsan, were employed as an input data for WRF-CMAQ air quality model for emission assessment. The simulated results were compared with observations for the local emission dominant synoptic conditions which had negative vorticities and lower geostrophic wind speed at 850hPa weather maps. The measurements of CO, $NO_2$, $SO_2$ and $PM_{10}$ concentrations were compared with simulations and the 'scaling factors' of emissions for CO, $NO_2$, $SO_2$, and $PM_{10}$ were suggested in in aggregative and quantitative manner. The results showed that CAPSS-2003 showed no critical discrepancies of CO and $NO_2$ observations with simulations, while $SO_2$ was overestimated by a factor of more than 12, while $PM_{10}$ was underestimated by a factor of more than 20 times. However, CAPSS-2010 case showed that $SO_2$ and $PM_{10}$ emission were much more improved than CAPSS-2003. However, $SO_2$ was still overestimated by a factor of more than 2, and $PM_{10}$ underestimated by a factor of 5, while there was no significant improvement for CO and $NO_2$ emission. The estimated factors identified in this study can be used as'scaling factors'for optimizing the emissions of air pollutants, particularly $SO_2$ and $PM_{10}$ for the realistic air quality simulation in Ulsan.

• Journal of the Korean Society of Urban Environment
• /
• v.18 no.4
• /
• pp.531-546
• /
• 2018

Air quality forecasting system with Asian dust emissions was developed in East Asia, and $PM_{10}$ forecasting performance of chemical transport model with Asian dust emissions was validated and evaluated. The chemical transport model (CTM) with Asian dust emission was found to supplement $PM_{10}$ concentrations that had been under-estimated in China regions and improved statistics for performance of CTM, although the model were overestimated during some periods in China. In Korea, the prediction model adequately simulated inflow of Asian dust events on February 22~24 and March 16~17, but the model is found to be overestimated during no Asian dust event periods on April. However, the model supplemented $PM_{10}$ concentrations, which was underestimated in most regions in Korea and the statistics for performance of the models were improved. The $PM_{10}$ forecasting performance of air quality forecasting model with Asian dust emissions tends to improve POD (Probability of Detection) compared to basic model without Asian dust emissions, but A (Accuracy) has shown similar or decreased, and FAR (False Alarms) have increased during 2017.Therefore, the developed air quality forecasting model with Asian dust emission was not proposed as a representative $PM_{10}$ forecast model in South Korea.

• Journal of Environmental Impact Assessment
• /
• v.27 no.5
• /
• pp.509-520
• /
• 2018

The impact of meteorological condition on surface $PM_{10}$ concentrations in South Korea was quantitatively simulated from 2010 to 2014 using WRF (ver.3.8.1) and CMAQ (5.0.2) model. The result showed that seasonal standard deviations of PM10 induced by change of weather conditions were $4.8{\mu}g/m^3$, $1.7{\mu}g/m^3$, $1.7{\mu}g/m^3$, $4.2{\mu}g/m^3$ for spring, summer, autumn and winter compared to 2010, respectively, with the annual mean standard deviation of about $2.6{\mu}g/m^3$. The results of 18 regions in South Korea showed standard deviation of more than $1{\mu}g/m^3$ in all regions and more than $2{\mu}g/m^3$ in Seoul, Northern Gyeonggi, Southern Southern Gyeonggi, Western Gangwon and Northern Chungcheong in South Korea.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.6
• /
• pp.563-576
• /
• 1998

To study the influences of the emission sources during lune 13∼15 1997 in Seoul, MESOPVFF II model has been used. The MESOPVFF II model includes terrain effects, chemical transformation and removal processes. Data of 20 surface meteorological stations and the upper air station on mid-west area in Korea were used as a DWM (Diagnostic Wind Model) input data. This model is likely to be applicable because the predicted SO2 concentration was well matched with measured 502 concentration in Seoul and Kyonggido. In generally air pollutants in Seoul have major influence on the other cities but the result of modeling appeared also air pollutants of the other cities influence on Seoul. Finally, in the case of calculating the air quality by diffusion model, the influences of air pollutants emitted in metropolitan area as well as the emission rate in modeling area should be considered.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.23 no.5
• /
• pp.488-496
• /
• 2017

Emissions of pollutants from ship-based sources are controlled by the International Maritime Organization (IMO). Since pollutants emitted from ship may be dispersed to the land, controlling emissions from ships is necessary for efficient air quality management in Incheon, where exposure to ship-based pollution is frequent. It has been noted that the ratios of air pollutant emissions from coastal areas to inland areas are about 14% for NOx and 10% for SOx. The air quality of coastal urban areas is influenced by the number of ships present and the dispersion pattern of the pollutants released depending on the local circulation system. In this study, the dispersion of pollutants from ship-based sources was analyzed using the numerical California Puff Model (CALPUFF) based on a meteorological field established using the Weather Research and Forecasting Model (WRF). Air pollutant dispersion modeling around coastal urban regions such as Incheon should consider point and line sources emitted from both anchored and running ships, respectively. The total average NOx emissions from 82-84 ships were 6.2 g/s and 6.8 g/s, entering and leaving, respectively. The total average SOx emissions from 82-84 ships, entering and leaving, were 3.6 g/s and 5.1 g/s, respectively. The total average emissions for NOx and SOx from anchored ships were 0.77 g/s and 1.93 g/s, respectively. Due to the influence of breezes from over land, the transport of pollutants from Incheon Port to inland areas was suppressed, and the concentration of NOx and SOx inland were temporarily reduced. NOx and SOx were diffused inland by the sea breeze, and the concentration of NOx and SOx gradually increased inland. The concentration of pollutants in the area adjacent to Incheon Port was more influenced by anchored ship in the port than sea breezes. We expect this study to be useful for setting emission standards and devising air quality policies in coastal urban regions.

• Journal of Korean Society for Atmospheric Environment
• /
• v.21 no.1
• /
• pp.97-105
• /
• 2005

In order to reduce the uncertainties and improve the air flow field, objective analysis using asynoptic observational data is chosen as a method that enhances the reality of meteorology. In surficial data and their numerical interpolation for improving the interpretation of meteorological components, objective analysis scheme should perform a smooth interpolation, detect and remove the bad data and carry out internal consistency analysis. For objective analysis technique which related to data reliability and error suppression, we carried out two quality control methods. In site quality control, asynoptic observational data at urban area revealed low representation by the complex terrain and buildings. In case of wind field, it was more effective than temperature field when it were interpolated near waterbody data. Many roads, buildings, subways, vehicles are bring about artificial heat which left out of consideration on the simulation of air flow field. Therefore, in temperature field, objective analysis for more effective result was obtained when surficial data were interpolated as many as possible using value quality control rather than the selection of representative site.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.236-236
• /
• 2016

현재 댐운영 계획 수립 시 매월 유지해야 하는 저수량의 범위를 나타낸 기준수위가 사용되고 있으며 매년 홍수기 말에 현재의 수문 상황과 장래의 전망을 통한 시기별 연간, 월간 댐운영 계획을 수립하고 있다. 물관리의 이수측면에서 댐수위 운영계획 수립과 홍수기 운영목표 수위를 결정하는데 활용하기 위해서는 계절단위, 연단위의 기상정보가 필요하다. 본 연구에서는 기상청에서 운영하고 제공하는 전지구 계절예측시스템 GloSea5(Global Seasonal forecasting system version 5)자료를 활용하여 금강유역에 적용하고자 하였다. GloSea5는 전지구계절예측시스템으로 대기(UM), 지면(JULES), 해양(NEMO), 해빙(CICE)모델이 서로 결합되어 하나의 시스템으로 구성되어 있으며 공간 수평해상도는 N216($0.83^{\circ}{\times}0.56^{\circ}$)으로 중위도에서 약60km이다. Hindcast자료는 유럽중기예보센터(ECMWF)에서 생산된 ERA-Interim 재분석장을 대기 모델의 초기장으로 사용하며 기간은 1996~2009년의 총 14년이다. 예보자료의 검증은 예보의 질을 결정하는 과정으로 Brier Skill Score (BSS), Reliability Diagrams, Relative Operating, Characteristics (ROC)등을 통해 정확성과 오차에 의한 예보의 성능을 검증하였다. 또한 Glosea5의 통계적 상세화를 수행하여 다양한 변수가 갖는 계통적인 지역 오차를 보정함으로써 자료의 신뢰도를 향상시키고자 하였으며 이는 이후 수문모델과의 연계 시 보다 정확하고 효율적인 댐운영에 활용할 수 있는 기후예측정보를 제공할 수 있을 것으로 판단된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.2
• /
• pp.271-277
• /
• 2017

As a result of rapid industrialization, air pollutants are seriously threatening the health of the people, the forecast is becoming more and more important. In forecasting air quality, it is very important to create a reliable initial field because the initial field input to the air quality forecasting model affects the accuracy of the forecast. There are several methods for enhancing the initial field input. One of the necessary techniques is data assimilation. The number of operations and the time required for such data assimilation is exponentially increased as the forecasting area is widened and the number of observation sites increases. Therefore, as the forecast size increases, it is difficult to apply the existing sequential processing method to a field requiring fast processing speed. In this paper, we propose a method that can process Cresman's method, which is one of the data assimilation techniques, in real time using CUDA. As a result, the proposed parallel processing method using CUDA improved at least 35 times faster than the conventional sequential method and other parallel processing methods.

• Journal of Environmental Science International
• /
• v.8 no.1
• /
• pp.135-144
• /
• 1999

Air quality modeling about coastal urban region such as Pusan shoud be consider shipping source emmited from ships anchoraging and running. It has been proved at our previous studies that the ratios of air pollutants emission amount in coastal area to inland are 12.2% for NO$_2$ and 11.7% for $SO_2$ and the air qualify of coastal urban area consierably counts on ships. Also the dispersion pattern of the all pollutants followed local circulation system in this region. Therefore this study has been developed air quality model which can describe the formation, transport, transformation and deposition processes of air pollutants considering shipping source. Currently, restriction for emission amount of ships does not exist, so our study will be useful to set the omission standard and for devising air quality policy in coastal urban region.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.6
• /
• pp.640-652
• /
• 2007

The MM5, RAMS and WRF, meteorological models have provided the dynamical parameters as inputs to air quality model. A major content of this study is that significant characteristics of three models for high-ozone occurrence analyze for surface wind and air temperature fields and compare with observation data in Seoul metropolitan area. An analysis of air temperature field revealed that location of core in high temperature of MM5 and WRF differed from that of RAMS. MM5 and WRF indicated high temperature in Seoul but RAMS represented it on the outskirts of Seoul. MM5 and WRF were underestimated maximum temperature during daytime but RAMS simulated similar value with observation data. Surface wind field with three models, it was shown many differences at horizontal distribution of wind direction. RAMS indicated weak wind speed in land and strong sea breeze at coastal areas than MM5 and WRF. However wind speed simulated by three model were overestimated during both daytime and nighttime.